How enterprises can transition their knowledge and systems for Agentic AI

As the adoption of agentic AI accelerates across industries, enterprise leaders face a crucial challenge: preparing today’s knowledge and systems for tomorrow’s AI-powered customer service.

Integrating distributed knowledge, ensuring information accuracy, and architecting AI agents are not just technical exercises—they are strategic imperatives for any organization seeking to stay ahead in the age of generative and agentic AI.

This article provides five key steps to future-proofing an enterprise for the agentic AI era.

1. The foundation: knowledge quality and ownership

At the heart of any effective agentic AI system lies one asset: organizational knowledge. Yet, as enterprises have grown, so too has the sprawl of knowledge—scattered across departments, tools, and formats. The first—and arguably the most difficult—step is consolidating this knowledge into one unified, accurate ...